Fast, Safe, and Cheap: Making Good AI Design Decisions

The model landscape has exploded — LLMs, SLMs, fine-tuned models, edge inference, classical ML — and the pressure to ship means most teams default to whatever they are familiar with. But fit-for-purpose AI isn't just about picking the fastest or cheapest option. Observability and explainability are architectural requirements, not afterthoughts, and treating them that way changes every decision downstream.

Fast, cheap, and safe don't have to be tradeoffs- this talk walks through decision frameworks to get all three.